Dependent Hamacher Aggregation Operators for Complex q-Rung Orthopair Fuzzy Sets and Their Application

Abstract

Complex q-rung orthopair fuzzy sets (Cq-ROFS) become one of the effective tools to deal with unresolved and complex information. In recent years, a variety of multi-attribute decision making(MADM) methods have been developed in the Cq-ROFS environment, such as complex intuitionistic fuzzy set (CIFS) and complex Pythagorean fuzzy sets(CPFS). Cq-ROFS is superior to CIFs and CPFS, which can describe a wider range of uncertain information spaces. Therefore, this paper studies MADM based on Cq-ROFS. However, decision making experts may have personal biases. In order to reduce the influence of individual preference on decision-making, the dependent Hamacher aggregation operators for Complex q-rung orthopair fuzzy sets(Cq-ROFDHA) are proposed based on the Hamacher operation and dependent method. The operator can improve personal bias by assigning lower weights to biased evaluations (unduly high or unduly low values) and higher weights to mid values. Firstly, the basic operation rules, score function, distance and properties of Cq-ROFDHA are described. We then applied Cq-ROFDHA to service utility decisions for online health communities. Finally, we compare it with other aggregation factors. The results show that the Cq-ROFDHA operator has the advantages of consistency and superiority.